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Gradient boosting is a useful machine learning technique that uses an ensemble of weak learners to produce high-quality predictions. In this SAS How To Tutorial, Christa Cody presents a high-level introduction to gradient boosting (i.e. no complicated math involved). Then, she builds a machine learning pipeline in SAS Model Studio containing a Gradient Boosting node and explores its options. Download Data Files Download the HMEQ data set that Christa uses here – https://support.sas.com/documentation... Chapters 00:00 – Welcome 00:14 – Single model example 00:35 – Explanation of ensemble methods: bagging and boosting 05:32 – Overview of gradient boosting 07:23 – Gradient boosting in SAS Learn more about SAS Software ◉ AI and Machine Learning Courses – https://www.sas.com/en_us/training/pr... ◉ SAS Viya Gradient Boosting Task – https://go.documentation.sas.com/?doc... ◉ How to train a forest model with Cat – • SAS Tutorial | How to train forest mo... ◉ Machine Learning Fundamentals with Ari – • SAS Tutorial | Machine Learning Funda... ◉ Data Mining and Machine Learning Community – https://communities.sas.com/t5/SAS-Da... ◉ Machine Learning Using SAS Viya e-Learning – https://learn.sas.com/course/view.php... SUBSCRIBE TO THE SAS USERS YOUTUBE CHANNEL #SASUsers #LearnSAS https://www.youtube.com/SASUsers?sub_... ABOUT SAS SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change. CONNECT WITH SAS SAS ► https://www.sas.com SAS Customer Support ► https://support.sas.com SAS Communities ► https://communities.sas.com SAS Analytics Explorers ► https://explorers.sas.com Facebook ► / sassoftware Twitter ► / sassoftware LinkedIn ► / sas Blogs ► https://blogs.sas.com RSS ► https://www.sas.com/rss